Causal or spurious: Using propensity score matching to detangle the relationship between violent video games and violent behavior

Throughout the past decade, numerous states have passed legislation to prohibit the sale of violent video games to children, usually in conjunction with an argument that exposure to violent media increases violent behavior. However, the link between video games and violence is not yet fully understood. This study uses propensity score matching as a method to more adequately address the underlying issue of causality. Using a sample of 6567 8th grade students, these analyses test whether there is a causal link between playing violent video games and violence, non-violent deviance and substance use. Results indicate a substantial decrease in the relationship between video games and these outcomes when a matched sample is used. This suggests that the strength of evidence supporting a relationship has likely been overestimated using other methodologies.     

An empirical study of the cross-channel effects between web and mobile shopping channels

With the increasing popularity of mobile applications, increasingly more e-commerce websites are providing mobile shopping services that enable their consumers to access their products and services through an additional mobile channel. The question arises here as to whether the new channel brings new sales or merely shifts consumers from the web to the mobile channel. Using the 2½-year transaction data obtained from an e-commerce company that expanded its web service onto a mobile platform, we investigated the impact of the newly introduced mobile channel on the sales of the incumbent web channel, and whether it could stimulate new consumption from consumers. Our empirical results indicate that after the adoption of the mobile channel, the purchases on the web channel were slightly cannibalized; however, the consumers’ purchases increased overall, suggesting that the positive synergy effect of the new channel overrode the negative cannibalization effect. Our investigation contributes to multichannel e-commerce literature by empirically testing the cross-channel effects of a new mobile channel and also providing insights for e-retailers interested in introducing a new mobile channel.     

“Understanding a fury in your words”: The effects of posting and viewing electronic negative word-of-mouth on purchase behaviors

Marketing scholars and practitioners have long recognized that the power of electronic negative word-of-mouth (e-NWOM) can influence brand revenues and firm performance, but most previous studies have only examined the effect of viewing. This study is one of the initial attempts to test the effects of e-NWOM on both posters and viewers. We also test the moderating effects of company usefulness and company apology in a separate study. Using an observational dataset that contains NWOM viewing and posting records and customers' purchase transactions from a real company, Study 1 finds that viewing e-NWOM has a negative effect on subsequent purchases, whereas posting e-NWOM has a positive interaction effect with company usefulness. Study 2 shows that a company's public apology has a positive effect on viewers, but not posters. We conclude with the theoretical, methodological, and managerial implications of e-NWOM and webcare research.     

The specification of the propensity score in multilevel observational studies

The use of multilevel models for the estimation of the propensity score for data with a hierarchical structure and unobserved cluster-level variables is proposed. This approach is compared with models that ignore the hierarchy, and models in which the hierarchy is represented by a fixed parameter for each cluster. It is shown, by simulation, that simple models with dummy variables outperform both random effect models and models ignoring the hierarchy in terms of balance of cluster-level unobserved covariates and omitted variable bias. The representation of the clusters by fixed or random effects defines a model more general than would be ideal if the relevant cluster-level variables were available. The general conclusion confirms that when conducting propensity score analysis it is safer to specify a more general model than pursuing model parsimony.     

Does online learning impede degree completion? A national study of community college students

Using a nationally representative sample (The Beginning Postsecondary Student Survey, BPS 04/09), this study examined the associations between enrollment in credit-bearing distance education courses and degree attainment. We sought to determine whether US students enrolled in distance education courses during their first year of study at a community college tend to complete a degree (certificate, associate, or bachelor's) at significantly lower rates than those who were not enrolled in such courses or programs. Consistent with previous large-scale research at the State level in Virginia and Washington (Smith Jaggars & Xu, 2010; Xu & Smith Jaggars, 2011), we hypothesized that community college students who participate in distance education in early semesters graduate at lower rates than students who do not. Contrary to expectations, the study found that controlling for relevant background characteristics; students who take some of their early courses online or at a distance have a significantly better chance of attaining a community college credential than do their classroom only counterparts. These results imply that a new model of student retention in the age of the internet, one that assumes transactional adaptation, may be warranted.     

普通话发音训练多级音素模板综合评价方法

提出了一种应用于普通话声韵母发音评价的多级音素模板综合评分法,该方法在单模板匹配的基础上,通过寻找汉语音素发音过程中的浊化、摩擦、爆破等特征,形成多个子模式,进行多模式匹配,最后给出加权评分。实验结果表明多级音素模板综合评分法有效地改善了汉语发音中几组相似音之间的区分度。也介绍了MFCC等语音特征提取、DTW模板匹配算法、基于聚类的模板训练以及综合加权评价机制的实现方法。     

基于故障树和规则匹配的故障诊断专家系统

当前对于设备的故障诊断专家系统,无论在设计上还是实现上,都受到很多客观因素的制约,使得专家系统的实用性和效率都受到了很大的影响。该文从实际应用的角度出发,在已有故障树诊断和规则推理诊断方法的基础上,提出了一种基于专家规则匹配的、可成长的故障诊断专家系统模型,并给出了基于该系统的推理算法和成长机制。该系统模型着重于提高诊断系统的效率和实用性,具有一定的通用性,并在实际项目中取得了较为成功的应用。     

学习高阶马尔可夫随机场：评分匹配方法

传统的马尔可夫随机场模型有两个内在的缺陷：邻域的低阶性和参数的手动选择。提出一种新的机器学习方法——评分匹配法,从训练图像数据中学习得到一组高阶马尔可夫随机场模型参数。为了验证通过学习得到的马尔可夫随机场模型的能力,将学习得到的参数向量通过贝叶斯规则应用于图像去噪。实验结果表明：不管是根据峰值信噪比的大小还是根据主观视觉,都能取得优秀的去噪效果,从而表明该学习方法的有效性。     

基于捷联惯导系统的杆臂效应误差分析

随着捷联惯导系统的发展,对惯性导航精度和快速性的要求越来越高。而快速性主要取决于初始对准时间。传统的初始对准方法具有一定的局限性,而传递对准是一种新型的、快速的初始对准方法。主要分析了传递对准方法中的速度匹配方法,在此基础上推导了杆臂效应的基本原理。最后通过仿真得到,存在杆臂效应时,航向失准角估计误差稳态值为-0.5°;通过实船实验得到,存在杆臂效应时,俯仰、横滚和航向角的失准角估计误差分别为-0.22°,-0.37°,-0.35°,从而验证了杆臂效应误差对失准角的影响。     

基于Petri网的流程变体合并方法

业务融合时往往需要将已有的多个流程合并,从而形成新的满足实际需求的业务流程,如何识别已有业务流的共性特征来消除流程冗余具有较大的实际应用价值.因此,提出了一种基于Petri网的流程变体合并方法.首先,由计算匹配分数算法计算多个流程变体间不同组合的匹配分数,由此来选定一对匹配分数最高的流程变体组合;然后,根据提出的合并算...     

浅谈石化行业仪表节能工作的开展

当前节能成为我国经济发展中的重要部分。随着我国节能工作的发展,各行各业节能意识不断增强。从仪表设计、选型、安装、维护、研究开发等方面融入节能理念,必然会成为今后仪表工作发展的一个方向,将会给企业带来潜在的巨大经济效益。本文阐述了仪表节能的途径和效果。     

基于构件技术的虚拟电子测量仪器实现研究

首先提出了虚拟电子测量仪器构件的定义及其结构模型,给出了虚拟电子测量仪器构件的五种组合运算及运算规则,并对运算规则进行了详细的形式化定义,从而确立了虚拟电子测量仪器软件系统的代数表达式。     

Effects of promotion cost sharing policy with the sales learning curve on supply chain coordination

Promotional activity has become increasingly more common in the service industry. This research considers a two-echelon multiple-retailer distribution channel under retailers’ promotional efforts and the sales learning curve. The competition between retailers arises from substitution effect due to shortages. This paper incorporates the idea of the sales learning curve into the promotion cost. The objective is to solve the retailers’ promotion and replenishment decisions under retailer competition and promotional effort with the sales learning curve. The current study considers promotion cost sharing as a mechanism to achieve coordination. The model shows that keeping the fractions of promotion cost sharing within an appropriate range increases profits for all parties. This work also discusses how retailer competition and the sales learning curve affect channel decisions and profits. Concepts from retailer competition and the sales learning curve, along with numerical studies on a few interesting cases help deliver several important managerial insights. These results should be a useful reference for managerial decisions and administrations.     

A minutia-based partial fingerprint recognition system

Matching incomplete or partial fingerprints continues to be an important challenge today, despite the advances made in fingerprint identification techniques. While the introduction of compact silicon chip-based sensors that capture only part of the fingerprint has made this problem important from a commercial perspective, there is also considerable interest in processing partial and latent fingerprints obtained at crime scenes. When the partial print does not include structures such as core and delta, common matching methods based on alignment of singular structures fail. We present an approach that uses localized secondary features derived from relative minutiae information. A flow network-based matching technique is introduced to obtain one-to-one correspondence of secondary features. Our method balances the tradeoffs between maximizing the number of matches and minimizing total feature distance between query and reference fingerprints. A two-hidden-layer fully connected neural network is trained to generate the final similarity score based on minutiae matched in the overlapping areas. Since the minutia-based fingerprint representation is an ANSI-NIST standard [American National Standards Institute, New York, 1993], our approach has the advantage of being directly applicable to existing databases. We present results of testing on FVC2002's DB1 and DB2 databases.     

基于虚拟仪器的强噪声滴灌管生产线的自动测量和控制

为了提高内镶式滴灌管加工和打孔精度,需要建立在线检测和控制系统。高精度电容测微仪通过A／D采集板将电压信号的微变传入计算机,然后利用Lab View软件中的虚拟仪器、虚拟噪声、虚拟滤波、虚拟信号处理等模块对真实生产线进行实时仿真,直到得到理想的测量和控制结果。虚拟仪器编制的自动测量和控制软件具有友好的用户操作界面,节约了试验成本,有效的排除了强噪声干扰,充分满足了生产线的检测和控制要求。     

基于模板匹配与Hough圆检测的仪表识别

随着自动化技术的不断发展,国内电力系统的自动化程度不断提高,无人变电站、无人配电房也逐渐普及.针对变电站中指针式圆形仪表的识别,提出了一种基于模板匹配与Hough圆检测的仪表识别方法.首先对图像进行预处理,将摄像头获取到的RGB彩色图像进行灰度化以及图像的局部直方图均衡化,将预先采集的仪表模板与待测图片进行两次模板匹配...     

像对匹配的模板选择与匹配

目的 图像模板匹配法常用于寻找像对间区域的对应关系,目前尚存的问题有：1）随着摄影基线的增加,待匹配区域在目标影像中有效信息逐渐降低;2）匹配区域的选择对匹配结果准确性影响较大。为了解决上述问题,提出一种基于分值图的图像模板选择与匹配方法。方法 首先利用图像多通道特征,提出采用抽样矢量归一化相关算法SV-NCC （sampling vector-normalized cross correlation）度量两幅图像间区域一致性,增加多通道特征间的有效信息对比,以此降低噪声与光照对模板匹配的影响。其次,在矢量空间中对图像进行分块聚类,将模板区域根据颜色特征分为几类,统计匹配图像的每个区域类中心颜色在待匹配图像中相似数量的倒数作为度量值,其值越大则颜色或颜色组合在目标图像中相似的概率越小,以该位置为基础选取模板进行匹配的准确率越高。最后,给出依据分值图排序模板区域的方法,并选取高分值区域作为最终的模板选择区域。结果 实验采用公共数据集从两个方面对本文方法进行客观评价：1）在摄影基线变换不大的情况下,SAD与SV-NCC方法的准确率均较高,达到90%以上。随着摄影基线的增大,采用SAD方法匹配准确率降低速率更快,在第6幅Graf图像的测试中匹配准确率低于20%,而SV-NCC方法匹配准确率高于40%;2）随着摄影基线的增大,落在高分值图区域匹配的正确率高于未落在高分值图区域匹配的正确率,由此可见高分值图区域的合理选择将提高模板匹配方法的准确率,验证了本文分值图与选择最佳模板匹配位置方法的有效性。结论 该方法从定量和定性比较上都体现了较好的像对匹配能力,其匹配结果适用于影像融合、超分辨率重建及3维重建等技术中的先期处理步骤。     

基于二维码匹配的指针式仪表读数识别方法

提出了一种基于二维码匹配的指针式仪表读数识别方法.该方法先实时采集高质量的仪表状态图像,同时获取二维码定位点信息以及与二维码相连接的数据库中存储的仪表类型信息,再根据二维码定位点信息对仪表图像进行快速倾斜校正,并利用二维码与仪表之间先验的几何位置关系快速提取图像中表盘所在的区域,最后根据获取的仪表类型信息,选择对应的仪表读数识别算法,以实现快速准确地识别仪表读数.实验结果表明：该方法能有效提高指针式仪表读数识别的准确率,尤其是对于复杂背景的仪表图像,该方法可用于电力系统中刻度均匀的指针仪表识别.